Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 1 June 2021 doi:10.20944/preprints202106.0008.v1 Multiscale Modeling in Smart Cities: A Survey on Applications, Current Trends, and Challenges Asif Khana, Khursheed Aurangzebb, Musaed Alhusseinc, Sheraz Aslamd,∗ aScience and IT Department, Government of Balochistan, Quetta 87300, Pakistan bCollege of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.(e-mail:
[email protected]) cDepartment of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia. (e-mail:
[email protected]) dDepartment of Electrical Engineering, Computer Engineering, and Informatics, Cyprus University of Technology, Limassol 3036, Cyprus Abstract Megacities are complex systems facing the challenges of overpopulation, poor urban design and planning, poor mobility and public transport, poor gover- nance, climate change issues, poor sewerage and water infrastructure, waste and health issues, and unemployment. Smart cities have emerged to address these challenges by making the best use of space and resources for the benefit of citizens. A smart city model views the city as a complex adaptive system consisting of services, resources, and citizens that learn through interaction and change in both the spatial and temporal domains. The characteristics of dy- namic development and complexity are key issues for city planners that require a new systematic and modeling approach. Multiscale modeling (MM) is an approach that can be used to better understand complex adaptive systems. The MM aims to solve complex problems at different scales, i.e., micro, meso, and macro, to improve system efficiency and mitigate computational complexity and cost.